Optimized Upload Strategies for Live Scalable Video Transmission from Mobile Devices

Research output: Contribution to journalArticleScientificpeer-review

Researchers

Research units

  • Polytechnic University of Turin

Abstract

Sharing live multimedia content is becoming increasingly popular among mobile users. In this article, we study the problem of optimizing video quality in such a scenario using scalable video coding (SVC) and chunked video content. We consider using only standard stateless HTTP servers that do not need to perform additional processing of the video content. Our key contribution is to provide close to optimal algorithms for scheduling video chunk upload for multiple clients having different viewing delays. Given such a set of clients, the problem is to decide which chunks to upload and in which order to upload them so that the quality-delay tradeoff can be optimally balanced. We show by means of simulations that the proposed algorithms can achieve notably better performance than naive solutions in practical cases. Especially the heuristic-based greedy algorithm is a good candidate for deployment on mobile devices because it is not computationally intensive but it still delivers in most cases on-par video quality compared to the more complex local optimization algorithm. We also show that using shorter video segments and being able to predict bandwidth and video chunk properties improve the delivered video quality in certain cases.

Details

Original languageEnglish
Article number7500047
Pages (from-to)1059-1072
Number of pages14
JournalIEEE Transactions on Mobile Computing
Volume16
Issue number4
Publication statusPublished - 1 Apr 2017
MoE publication typeA1 Journal article-refereed

    Research areas

  • DASH, live video, mobile video streaming, scalable video coding, video transmission, video upload

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